Publication details

Testing of features for fatigue detection in EOG

Authors

NĚMCOVÁ Andrea JANOUŠEK Oto VITEK Martin PROVAZNÍK Ivo

Year of publication 2017
Type Article in Periodical
Magazine / Source BIO-MEDICAL MATERIALS AND ENGINEERING
MU Faculty or unit

Faculty of Medicine

Citation
Doi http://dx.doi.org/10.3233/BME-171683
Field Physiology
Keywords Biopac; blink; electrooculography; REM; scenes; SEM
Description The article deals with the testing of features for fatigue detection in electrooculography (EOG) records. An optimal methodology for EOG signal acquisition is described; the Biopac data acquisition system was used. EOG signals were being recorded while 10 volunteers were watching prepared scenes. Three scenes were created for this purpose a rotating ball, a video of driving a car, and a cross. Recorded EOG signals were processed and 20 features were extracted. The features involved blinks, slow eye movement (SEM), rapid eye movement (REM), eye instability, magnitude, and periodicity. These features were statistically tested and discussed in terms of fatigue detection ability. Some of the features were compared with published results. Finally, the best features - fatigue indicators - were selected.

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